{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2019 年 Pandas 官方用户调研\n",
    "\n",
    "为指引 Pandas 未来开发方向，Pandas 官方团队于 2019 年夏搞了一次调研，这次调研历时 15 天，共有 1250 条反馈数据。问卷数据保存在 `data` 文件夹的 `2019.csv.zip` 文件里。\n",
    "\n",
    "这里又学一招，原来 pandas 可以直接从压缩文件里读取数据文件，原文用的是 .gz 文件，呆鸟这里用 .zip 也可以。\n",
    "\n",
    "下列代码读取问卷数据，并对 matplotlib、seaborn 的字体进行设置，其中还包括了，如何在 macOS 里显示中文。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-18T02:28:19.398886Z",
     "start_time": "2019-09-18T02:28:19.386881Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "plt.rcParams['figure.dpi'] = 150\n",
    "\n",
    "# 让 matplotlib 支持中文\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "\n",
    "# 让 seaborn 的文字大一些\n",
    "sns.set( font='SimHei', font_scale=1.2)\n",
    "\n",
    "# # 让 MacOS 下的 Matplotlib 与 Seaborn 支持中文\n",
    "# plt.rcParams['font.family'] = ['Arial Unicode MS']\n",
    "# sns.set_style('whitegrid',{'font.sans-serif':['Arial Unicode MS','Arial']})\n",
    "\n",
    "\n",
    "# 用来正常显示负号，这里其实用不上\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "df = pd.read_csv(\"data/2019.csv.zip\", parse_dates=['日期时间'], encoding=\"GBK\")\n",
    "\n",
    "# df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-18T02:28:44.088758Z",
     "start_time": "2019-09-18T02:28:44.029734Z"
    }
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"data/2019.csv.zip\", parse_dates=['日期时间'], encoding=\"GBK\")\n",
    "\n",
    "# df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 答卷人分析\n",
    "\n",
    "绝大多数答卷人都具有丰富的 pandas 使用经验，使用频率也很高。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-17T09:06:11.992819Z",
     "start_time": "2019-09-17T09:06:11.759796Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "order = [\n",
    "    '少于 3 个月',\n",
    "    '3 个月 至 1 年',\n",
    "    '1 至 2 年',\n",
    "    '3 至 5 年',\n",
    "    '5 年以上',\n",
    "]\n",
    "\n",
    "sns.countplot(y='您用 pandas 多久了？',\n",
    "              data=df, order=order,\n",
    "              color='k').set(title=\"您用 pandas 多久了？\",\n",
    "                             ylabel=\"\")\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-17T09:06:12.179838Z",
     "start_time": "2019-09-17T09:06:11.995820Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "order = [\n",
    "    \"刚开始用\",\n",
    "    \"偶尔\",\n",
    "    \"每周\",\n",
    "    \"每天\"\n",
    "]\n",
    "\n",
    "sns.countplot(y='pandas 使用频率', data=df, order=order,\n",
    "              color='k').set(title=\"pandas 使用频率\",\n",
    "                             ylabel=\"\")\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "为了对比 Pandas 与 Python 的流行度，我们的问卷里提出了一些 [Python 开发者调研问卷](https://www.jetbrains.com/research/python-developers-survey-2018/)问过的问题。\n",
    "\n",
    "90% 的答卷人把 Python 作为主开发语言，Python 软件基金会调研报告里的数据为 84%。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-17T09:06:12.220842Z",
     "start_time": "2019-09-17T09:06:12.183839Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "是    90.67%\n",
       "否     9.33%\n",
       "Name: Python 是您的主打语言吗？, dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pct_format = \"{:0.2%}\".format\n",
    "\n",
    "df['Python 是您的主打语言吗？'].str.replace(\n",
    "    \"否.*\", \"否\").value_counts(normalize=True).apply(pct_format)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-17T07:41:03.206542Z",
     "start_time": "2019-09-17T07:41:03.187542Z"
    }
   },
   "source": [
    "数据显示 Windows 用户居多。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-17T09:06:12.250845Z",
     "start_time": "2019-09-17T09:06:12.225843Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Linux      61.57%\n",
       "Windows    60.21%\n",
       "MacOS      42.75%\n",
       "Name: 您用哪种操作系统？, dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oses = [\n",
    "    \"Linux\",\n",
    "    \"Windows\",\n",
    "    \"MacOS\"\n",
    "]\n",
    "df['您用哪种操作系统？'].str.split(';').explode().value_counts().div(len(df)).loc[oses].apply(pct_format)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[conda](https://conda.io/en/latest/) 是最流行的虚拟环境工具。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-17T09:06:12.264847Z",
     "start_time": "2019-09-17T09:06:12.258846Z"
    }
   },
   "outputs": [],
   "source": [
    "def split_and_explode(s):\n",
    "    return s.str.split(\";\").explode().to_frame()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这里用 0.25 版推出的 `explode` 方法定义了个函数。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-17T09:06:12.479868Z",
     "start_time": "2019-09-17T09:06:12.270847Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "replace = {\n",
    "    \"否，我不用虚拟环境\": \"否\"\n",
    "}\n",
    "\n",
    "col = '您是否用过下列 Python 虚拟环境工具？（多选）'\n",
    "\n",
    "sns.countplot(y=col,\n",
    "              data=split_and_explode(df[col]).replace(replace),\n",
    "              color='k').set(title='您是否用过下列 Python 虚拟环境工具？',\n",
    "                             ylabel=\"\")\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "绝大多数答卷人只用 Python 3。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-17T09:21:50.462657Z",
     "start_time": "2019-09-17T09:21:50.451656Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3        92.39%\n",
       "2 & 3     6.80%\n",
       "2         0.81%\n",
       "Name: Python 2 还是 3？, dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Python 2 还是 3？'].value_counts(normalize=True).rename(\n",
    "    index={\"2;3\": \"2 & 3\"}).apply(pct_format)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pandas API\n",
    "\n",
    "开源软件团队很难了解用户实际爱用哪些功能，这次调研，我们提了一些问题，了解了大家的喜好。\n",
    "\n",
    "CSV 与 Excel 是最流行的文件类型，真是让人喜忧参半。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-17T09:47:45.725082Z",
     "start_time": "2019-09-17T09:47:45.382082Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(y='您常用哪个读写器读取数据？',\n",
    "              data=df['您常用哪个读写器读取数据？'].str.split(';').explode().to_frame(),\n",
    "              color='k').set(title=\"您常用哪个读写器读取数据？\",\n",
    "                             ylabel=\"\")\n",
    "sns.despine();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "为了做好重构 pandas 内核的准备，我们还调研了 100 列及以上大型 DataFrame 的处理情况。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-17T09:54:57.662371Z",
     "start_time": "2019-09-17T09:54:56.552260Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ZWZMNGDaSdgf2Ba6vFD8K3JrX31jS/bn8kvz1LaQQOKqyzknAP4GP5ekpwBcr898PnEYKE0jdXp0RsSi3bF4dEY9LupuVu8TagMciYqdc31o32k6VY+jFzMyaZjAtmz8A7wA+UyuIiF0AJE0jt2yqK0TERZJ+BIyXtFVE3AUsJoeEpI0i4st1+9mb1DKqhU07cFsOik2A3+SWzVRgTGW9kYM4BjMza6IBwyYiFgG31O65SPoFMJ0UHvUtmw2Az0fEVyKiR9KZwFbAXrXtSWoHbpV0XET8pLKfp+ru6xwIPEwKu7kRsQ2NrUPqRrs9T7cDm1amzcysyVbloc6lwDsjYhpp9NlNwLuADwBnkEIISW8D3kQaYfaMiFgCHAl8V9KO/eznUeBCUpfcvf0sNxn4XURMzyPQ3gw8VJuujkozM7PmWJWw6SG1JM4GvgG8LH/9BjAeQFIn8B3gHRHxQP0GIuIa4FTgckmTG+0kIm4GjiYFzs391KeTdP/IzMzWUkMJmxGVf48B1wAnApMjYmfScy89pNFjXwY+EhHX1a2/vDJ9Gmm02bGVstHkezCSRgO7k4JmH0nfl/QaSRPq6nUIcEXdfmrbaJM0Ke932RCO1czMhtFQwqadFAbtABHxo4j4Y0QszPOnAa8FbgT2iYgfAEh6oaTPAgdQeao/InqBg4BPVPYxBmiXtB/wO+Ap0sCB6aTWy8nAQ5IuzNveF1g3Iq6tbKMNqL0pYHugGzg/Ihw2ZmZN0tbbW3ZUsKTxwLdJQ6fPySEz0DrtpFfSLOxj/jOvspG0WUR097FcGzA+IuYNsdrTgPs6Ozvp6uoa4qpmZq2ru7ub2bOfXuX1OzomtDUqLx42LWoaDhszex4qFTb+iAEzMyvOYWNmZsU5bMzMrDiHjZmZFeewMTOz4hw2ZmZWnMPGzMyKc9iYmVlxDhszMyvOYWNmZsU5bMzMrDiHjZmZFeewMTOz4hw2ZmZWnMPGzMyKc9iYmVlxDhszMyvOYWNmZsU5bMzMrDiHjZmZFdfW29vb7DqsjaYB9zW7EmZma9qCBQuZP3/ZKq/f0TGhrVH5qFXe4vPAnDnz6OlpzTDu6JjA7NlPN7saq6XVj6HV6w+tfwytXn94bhwDuBvNzMzWAIeNmZkV57AxM7PiHDZmZlacw8bMzIpz2JiZWXEOGzMzK85hY2ZmxTlszMysOIeNmZkV57AxM7PiHDZmZlacw8bMzIrzW5/7sdFG6za7Cqulo2NCs6uw2mrHsLqvPTez5nLY9KOzs5Ourq5mV8OA7u5u5s9v/desmz1fuRvNzMyKc9iYmVlxDhszMyvOYWNmZsU5bMzMrDiHjZmZFeewMTOz4hw2ZmZWnMPGzMyKc9iYmVlxDhszMyvOYWNmZsU5bMzMrDiHjZmZFeewMTOz4hw2ZmZWnMPGzMyKc9iYmVlxDhszMyvOYWNmZsU5bMzMrDiHjZmZFTeksJG0kaRRlenxkl4vafQg1v0/SfuuSiUH2O4mkqb3Ma9DUq+k9YZ7v2ZmNnijBl5kJWcCfwG+lKcnAlcD6wBLB1h36UDLSDoc+BrQVdn+OKA7T48HnoyIHSurnQi8DHhlg00+Vdm3mZk1yVDDZhkwtzK9HFgcEYvqF5R0F+kkvzwXvRj4tqR5pBbV+sDHI+LCymqLgCsi4l/zNv4D2DUiDsvTewOn1e3qc8Ddkt4KXAksi4iePK8WMm2Sxjaqp5mZlTfUsOkFFlSmRwINu9AiYuvqtKSbgE9ExHX9bL+nn3kNl4mIxyR9jtS6+gxwuKT67dwNtAFTBrF9MzMbZkMNm3WBhZXpccAISRMi4ulhqM9yYH9Jt+bpDmB8ZXoC8M/awpJGRERPRHy5UnYW8ERELMjTvcBWbtWYmTXPUMNmIqmFUDM5f90G+H2tUNJfSK2eWgtjDLAF8D+SnshlI0j3YE6MiB/ksjbgqgG60Wr3iwD+LbdqxubtzAAuAH5Wt5yZmTXRUMNma+Arkm6NiHuBnUktnT2phE1EbFf7XtLkPO8JUih8NCKu6mP7I4dSmYj4Nuk+0CzS/SRIAwzOkXRmrXVjZmbNNeiwkfQSUhh8FvilpFcCbwA+Dxwl6asR0Vu3zhjgf4AZwIHAucB3JL02Iu5ssJt1gAMk3Z6nJwLjKtPjgUcHqOolQDuwZLDHZmZmZQ3lOZt/B86LiHOAXwPHk1s6pBP7wdWFJY0DLiWNXqvdU7mDFE7XSHpVg31MBs6MiOkRMT0ve1ll+vCBKhkRvXmE2yhJLyQNalg+wGpmZlbQoMJG0g7Ae1gRGu8DdgROj4glwCnA1yVtlJd/OXALaejxv1SGIhMRZ5GGL/9C0vmSXl3ZVSdwK0MgaX1g+/yvagbwd+DiiPBzNmZmTTRg2EjaBPgJ6ZmYR3LxCaSRaTMAIuIiUkhcLWmzXH4Z8NaIWJzXGV3bX0ScQXoIcxNg27yfDYHdgevr6jcyzx8BTAJq26vV7XrgEWBXSTdJOjK/UeBUYCrwn5KmSeqU5KHPZmZNMJh7Nm3AjIj4HoCkfyO1bPaIiGWV5Q4FrgVeAbyqbh6khzjbaxMRcSvwusr840mtkKcqZUtZ8VzPh4AvAB+tzN+P9AzNO3M9DwUOI7W0JpAGJNQCtZcUbmZmtoa19fb2DrxURb7pPzkiHmgwrz13qw1Z3u6EiHi8j/nrAEvrQ0zSqAbBtrqmAfd1dnbS1dU10LK2BnR3dzN79nA8yrXmdHRMaLk612v1Y2j1+kPrHUNHx4S2RuVDHfpM7hZ7VtDkeas8Aixvd3E/8xf2UT7cQWNmZsPMHzFgZmbFOWzMzKw4h42ZmRXnsDEzs+IcNmZmVpzDxszMinPYmJlZcQ4bMzMrzmFjZmbFOWzMzKw4h42ZmRXnsDEzs+IcNmZmVpzDxszMinPYmJlZcQ4bMzMrzmFjZmbFOWzMzKw4h42ZmRXnsDEzs+JGNbsCa7Obb7652VWwbMGChc2ugpmtBodNP+bMmUdPT2+zq7FKOjomMHv2082uxmp5LhyDmSXuRjMzs+IcNmZmVpzDxszMinPYmJlZcQ4bMzMrzmFjZmbFOWzMzKw4h42ZmRXnsDEzs+IcNmZmVpzDxszMinPYmJlZcX4RZz822mjdZldhtXR0TGh2FVZbqx9DM+u/YMFC5s9f1rT9m1U5bPrR2dlJV1dXs6thtkq6u7uZP99vzba1g7vRzMysOIeNmZkV57AxM7PiHDZmZlacw8bMzIpz2JiZWXEOGzMzK85hY2ZmxTlszMysOIeNmZkV57AxM7PiHDZmZlacw8bMzIpz2JiZWXEOGzMzK85hY2ZmxTlszMysOIeNmZkV57AxM7PiHDZmZlacw8bMzIpz2JiZWXGDDhtJIyUdKWnUIJcfK+mLkkbn6ZmSjs7f7yrp432s93FJL6gr+7GkqYOtq5mZrV0GFRzZPsCHge9J2hq4BngS6CGFVjuwV0R0A0TEIkkvAU4GPgUsyf8ATsjrr0TS+sBJwPmSRkRET561G7AsLzMKGBkRi/P0lsDfgMjLtgPTclnNtsDEiJg7hOM1M7NhMpSwOQb4ZF4nImKz2gxJ3wDWrQWNpCOBnUghNF3S2cAe+fudgf2AR3L5lRFxed7UocC1ef5xkpbn8g7gV3l6NHAbcEietwh4NCKm531vDVxdm85lvawIOjMzW8MG2yW2BzA+Iq6Q9GFSy+HYPO9A4B3A9pVVXgU8CFxYKat+/4P89TBgR+Dy3GL5MHBjRMwEZlb23wXsGRGPN6heT4OyRga7nJmZDbMBw0bSBsC3gH+T1A68j9yqkLQPcC4wB9gB+GVebTRwJ3AE8JI+Nn0xcH+lDocDG1b2uwy4A+gFJgHX5pbNNsD2EVHrNlsOTJJ0a54eC0ypTJuZWZMNpmWzITCVFDhbAR8A7pX0aeAo4O3Ao8APJP0K+AQpOJblZY8H7q7b5sHACyLi2ErZ+4HTSGECqdurM9/76QJeHRGPS7qblbvE2oDHImInWKkbbafaArkbzczMmmTAsImIe4H1JO0OHBgRP5D0BWAMsF1EPAmQ78WcBuwQETflsvZctqBus1N49gCBvUndb7WwaQduy0GxCfCb3LKZmvddM3KQx2pmZk0ylHs2pwH/JelY4BLgZ8AbJY0kdWW1ke633FRZ9Q2kLjWAz5NGjJ2Xp+dV9xERT0mqFh0IPAz8AZgbEdvQ2DqkbrTb83Q7sGll2szMmmww92zagDNJ4bAvcBfQHRGb5PkzgRsiYlbder8ANmPFjfkppJFj/1rbt6Q/RcTBfez6UdKggo8C9/ZTxcnA7yJir7zfvkajmZlZkwymG60XeHltWtImg1mPdK/noIi4Pa83A7g9Is7O028E/qOf/d6cHwL9CTCrn/10Ah4MYGa2FhtMy2YT4HPAC4GXAk8Ap7DyUOZG2vrY3ijgtaRnaZ6umz2afA8mv3lgd+BmYB9J3we+D9wSEdX1DgGqbyMYUdlGG+kZneXkh0LNzGzNG8zrah4jDVE+HXhJ7p76mKS/5vsiBwAnS7pd0j2Sjsjrzcrr1owBxkTEMtLDmyOBT9ftawzQLmk/4HfAU6SBA9NJrZeTgYckXQggaV/Sw6TXVrbRBtTeFLA90A2cn/drZmZN0Nbbu/bdzsij2EZGxMI+5j/zKhtJm9XeXNBguTbSw6jzGs3vxzTgvs7OTrq6uoa4qtnaobu7m9mz6zsPhqajY8Jqb6OZWr3+0HrH0NExoWGv1lBeV7PGRES/r5apvDONvoImz+ulbtSbmZmtef6IATMzK85hY2ZmxTlszMysOIeNmZkV57AxM7PiHDZmZlacw8bMzIpz2JiZWXEOGzMzK85hY2ZmxTlszMysOIeNmZkV57AxM7PiHDZmZlacw8bMzIpz2JiZWXEOGzMzK85hY2ZmxTlszMysOIeNmZkVN6rZFVib3Xzzzc2ugtkqW7BgYbOrYPYMh00/5syZR09Pb7OrsUo6OiYwe/bTza7Gamn1Y2j1+psNJ3ejmZlZcQ4bMzMrzmFjZmbFOWzMzKw4DxBobCTAiBFtza7Hamn1+kPrH0Or1x9a/xhavf7QcscwDegCllUL23p7W3O0VWF7AL9pdiXMzFrUlsD91QKHTWNjgJ2Bh4HlTa6LmVmrccvGzMzWPA8QMDOz4hw2ZmZWnMPGzMyKc9iYmVlxDhszMyvOYWNmZsU5bMzMrDiHjZmZFed3o9WR9HrgG8B4YEZEnNrkKvVJ0g7AeRGxXZ4eC3wb2A+4G3h3RNyb5+0EzASmABcBR0dE057olXQk8HlgY+DnwHuAucDpwKHAI8BhEXFbXn4r4PvA1sAvgSMioqkfRSnpxcBngc2BX5OOZyktdAwAkjqAO4BdgH/QQvWXdAGwL+nnDnAOcDItdAwAkq4CfhkRX5E0ghar/2C4ZVMhaQrwY+AjpHf77Cdp3+bWqjFJuwCXARMqxacCU4EtSH9w5+Vl18nLfosUNhsB71uD1V2JpJ2BTwNvBiYB44BPAR8C9if9IR0CXCBpdF7tYuDGvPx9wIlruNorkTQeuBr4KXA4sCvwMVroGCrOATry961W/52B7SNicv53Ei12DJIOJ/1dfj0XtVT9B8ths7K3AX+IiCsjYglwBvDuJtepL8cBH6grezfwuYhYGBH/C4yXtCXwatJ7is6OiB7gyzT3uJYC74yIWyLin6ST9pa5Tl+OiDkR8RfgTmAPSS8FXko6tl5S/Q9pUt1rpgCnRsQFEXEPcDkgWusYkHQYsD6pRQMtVH9JE4F1IqK7blYrHcMUUivmqIiovUusZeo/FA6blW0B3FqZvpd0dbE2ehep6wN4pgutg8b13wK4rdJt1tTjiog/RsQtlaI3ANfT989/C+CvEbEgr/8EsJ6kcWuoys8SEXdHxEwASduSWorn00LHIKnWAn4vUPvdaJn6k7r91pF0n6THJV0gaQKtdQxnkl72e4Kkr0maTGvVf9AcNisbSbpvUDMf2KBJdelXg/stI4GeiHiqUlar/1p7XJIOJv0RnUPf9awvB1hAuiJvKkn7A9cBT5Lu27TEMUhqA2YBJ0TEg5VZLVH/bATwFVaciNcjdce2xDFIegXwDlJ397eATUi/Q2NogfoPlcNmZU+w8n/cOBLm9/kAAAQqSURBVKCnSXUZqgXAUknrVcpq9V8rjyvf7JwBvCff5OyrnvXl1XlNFRFXAZsBD5C6Q1rlGI4GHo6IC+rKW6X+RMRVEfGFiFicr/a/SRoc0yrHsCfwx4g4LiKuJg2S2YwUmq1Q/yFx2KzsRuBVleldSCeRtV5u6fyW9AtMHtHyClL9fwvsJqk2+rDpxyVpA9J9ji9ExA25uK+f/5+AaZI2zOu+CGgHHl9zNV6ZpBdJ2hUg39/7EbAjrXMMBwH7SnpE0iOkgSW35Dq1Qv2R9JZ8T7Jmc1KXVKv8HywldZEBEBHLc9n1tEb9h8SfZ1ORuxb+ShoafB2pm+GkiPhBE6vVJ0nTgOsiYlqefhdpKO77gAOAAwFFRI+kq0m/sLOA/wYujYjPNaHa5JE1vwIiIo6slO8O/IQ05HMb4CTghRExV9LZwGTgi6Qhxt0RccQar/yKuu5KCstdgAeB/yH9fC+lRY6hStL9wN7AprRI/SWdCGwHHEWq9yXAd0mfsrvWH0Nu2f8O2DMi/ibp/cDxpBbOWl//oXLLpiK3DvYHppO6d85ZW4OmkYi4kDR88uvADsCb8+gzSCNcRpOetbmWNEy6WfYjffT22/ON3ccl/SYifgt8EDgFeDvwxoio9VEfSxrq+T3SpwAe04R6PyMibiKdBH5NCpsnSRcmLXMMjbRY/U8DFue6XA6cC3ylVY4hPwN3FHCxpMfz9+9olfoPlVs2ZmZWnFs2ZmZWnMPGzMyKc9iYmVlxDhszMyvOYWNmZsU5bMzMrDiHjdlznKRpkvyMgzWVw8bMzIrzQ51ma1j+SIJvAi8H7iF9aur1+fXy3wReQ/p8meMj4ud5nftJn9h4XZ4+GZgWEYdJug74IfBK4K15m+8kvT6n0ac4vi0iLi10eGYNuWVjtgblz1v5OemdWNuQXi9/af5MkstIr1/ZEfgqcLmk6YPc9GeA20mvWpoLfDIiFgETSa8uIn8/EfjZ8ByN2eCNGngRMxtGbyS9mfiT+QWpZ5LecbUz8DLgdRHxNDBL0huBfyd9TPBAfh8RpwJIOp/04XrklzduUPt+2I/GbJDcsjFbs6YCD9RekBoRS/ILVDcBHstBU3M36UPBGqn/dMZfVL5fDLQNU33NhoXDxmzN+gfpM0me+duT9GvgUWBS7mareTErPneol/RJjTU71233KfrWk/fjALKmcdiYrVk/I/3dfVHS5pI+CGxP+hylPwDn5KHKh5E+k+hbeb0HWfHBeIcAuw5hnw8B84A3S5oqac9hORKzIXDYmK1BuZvs9cBuwJ3A4cCbImI2aSTZGNInMh4LvCUi7sirfhJ4j6QgfR7QN4awz2XAEaTPaLoHOGxYDsZsCDz02czMinPLxszMinPYmJlZcQ4bMzMrzmFjZmbFOWzMzKw4h42ZmRXnsDEzs+L+HyeYvf4qk1lhAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(y='处理 100 列及以上大型 DataFrame 的频率',\n",
    "              data=df, color='k').set(title=\"处理大型 DataFrame 的频率\",\n",
    "                                      ylabel=\"\");\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pandas 增加新扩展类型的速度较慢。类别型（Categorical）是最常用的，此外，可空整数（Nullable Integer）与带时区的 Datetime 也很常用。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ShiZfI/V+vVXeG5kn7B8g6aRSIM9tsUM7x7YuqGlp8fPWzMx6SmnYqZUhtj5L0vKkgPS3aPuJ6aVth0ZEu3dGKj3Lat+IODm/3hbYGzisNGyYl48gBY+NgP3zHXq7ApsCPy/dTar0ANWfkYLk43lZDenmhzsjos3PkszbLVF+3la2WZJ040GH3zNJgzpqo2rkGzie7epdhnmu4axWhgy7TenO0SHttZn1DIcwMzMzswL01EP/zMzMzKwTHMLMzMzMCuAQZmbVGkx69pNv6DEz6wH+x9TMqrUKMGXGjNk0N3suaUeWXnpJ/vMfz2uuhtuqc9xe1esrbVVbO6LVR4e4J8zMbCEYPLitj3C0Sm6rznF7Va+vt5VDmJmZmVkB/IgKM6vWWFr/YGgzs0VaU9McGhvnd3n/toYjPSfMzDqlrq6O+vr6osswM+s1DQ0NNDbO6vHjejjSzMzMrAAOYWZmZmYFcAgzMzMzK4BDmJmZmVkBHMLMzMzMCuAQZmZmZlYAhzAzMzOzAjiEmZmZmRXAIczMzMysAH5ivg0Ykj4K/C+wNvAUMD4i+sWj3yVNi4jRPXSsscCkiBjbE8czM7OucU+YDQiSaoBbgT8BtcD/Ab+oYr9dJK23kMvrUE8FMDMz6zscwmyg+CywOvCTiGgGfgl8QdLQDvbbBSg8hJmZ2aLHw5E2UHwaeDEi5gJExAxJmwEtkiYA2wDzgLMj4iJJewEXACOBXSWdCZwZEecDSDoIOAFYCrgDOCQi5kkaBvwK2Bj4OzATaIiIwyXVAT8HVgEm532m5eO9DOwDHAesExGrlxcvqSUiaiqWHQD8ABgB/BE4KCKaJI0CrgU+AzQB342IG3uiEc3MrOe4J8wGimWA2eULIuIhYCtS0BoDrAucKml4RFyfhwCvB46KiNFlAWwccDSwCTA273twPuz+wNyIWIkUtJ7LAWwU8DvgFGBFUkC7rqLGS4ErgQ07upgcIH+S6x9DGmI9Jq/eHXgVWBn4InBRR8czM7Pe554wGyjmAouXXkhaDLiQ1JM0CzgJ2JTUs7UcFYGtwvak8PVMfr048FL++l1g8Xz8YUBjXv454M2IuCOf/yxghqSlImJm3uaciJhY5fXsCNwcES/n118sW/dLoAE4A9gcWKHKY5qZWS9yT5gNFAGsnifoQwpahwFHARcDzwMHAa9Ucawa4OrcOzYaWAk4vuw8awP1wMeBcztR4wOd2LZyaHIdSTvllxfleh4l9YqZmVkf5BBmA8XdpF6qo3IQO4IUejYE/gDcCGwErFqx3xvAagCSls/LJgK7SFpV0iDSYy9OyusOAo6LiJUiYoeIeCsvfxhYTtL2+fwnAPeW9YJ11u+B3SSNkTQYOJnU2wap9+u3uc69u3h8MzNbyBzCbECIiDnAFqS7HV8nTZz/GnA+8BVSz9VWwD+BNcp2vZB0F+UbpFBDRPwJOA2YBEwFFpDmekEKdL+R9KqkFyX9RtIyEfE2sBPwY+C1fI59u3E995OC1yRS711TPjakYcgf5WtZAZgtaY1WDmNmZgWqaWlpKboGs0WGpCeAPSLiZUlLkELZ1RFxTcGl9YSxwJS6ujrq6/vFM27NzHpEQ0MD06fP6vL+tbUjalpb7on5Zj3rf4F7cgBrBh4i3RVpZmb2AQ5hZj0oIi7Cj4QwM7MqeE6YmZmZWQEcwszMzMwK4BBmZmZmVgCHMDMzM7MCOISZmZmZFcAhzMzMzKwAflirmVVrLDCl6CLMzHpbU9McGhvnd3l/P6zVzHrEjBmzaW72f946Uls7oltP2B5I3Fad4/aqXl9vKw9HmpmZmRXAIczMzMysAA5hZmZmZgVwCDMzMzMrgEOYmZmZWQEcwszMzMwK4EdUmFmnLLvs8KJL6LO6+ywhMxtYHMLMrFPq6uqor68vuow+qaGhgcbGvvtMIjPrWzwcaWZmZlYAhzAzMzOzAjiEmZmZmRXAIczMzMysAA5hZmZmZgVwCDMzMzMrgEOYmZmZWQEcwszMzMwK4Ie1mvUiSV8CzgGWBv4MfD0i/ltsVWZmVgT3hJn1EklLA9cBuwCrkH7/vltoUWZmVhiHMLPe8zHS79zLEbEAOBF4uNiSzMysKB6ONOs9zwFvAA9KOiUi7gSekzQJeAnYAhgGnB4RPweQ9GngSmAlYBrwtYh4Lq+bBJwH7ErqXVshIt6VtAxwDbAB0AycFREX5n0+B1wAjAWeAcZHxCsL/9LNzKySe8LMeklEvANsDDwC3CDpQUkr5dWrAmsBmwOnS9ogLz8IuCoiVgJ+DpxUcdhzgPuA1SPi3bxsf2AksDIpiG0jaUgOZzcAhwArkHrhftbzV2pmZtVwCDPrRRExIyKOIQ1NzgWuzasujYh3I+Il4F5g07z8WGC2pEuB75PCU7lrI+KaiHizbNkjwBrA2cDngL0iYh4pAC4PTAQagENJwc/MzArgEGbWSyQdJunnABHxBnAMsFFeXf67uBiwQNJiwKOkIHVL3r7SA5ULImIysDbwGLAd8LykkUBNWh2jI2I0MBrYrCeuzczMOs8hzKz3vAB8WdJq+fUupJAF8E1JQyV9nDQ37AHSYyzWJc37ehzYt5qTSDoROB64ETgOGEWaA/YIMFrS1nnTw4C7unlNZmbWRQ5hZr0kIv4EnAn8SdJrpOHBA/PqF4G/AX8Cjo+IZyJiBimAPUrq1fo38DFJQzo41RWkYcZppOB3JfBMRLxFmsR/Vj7/nsB+PXiJZmbWCTUtLS1F12A2oOW7HE+JiEkFl9KRscCUuro66uvri66lT2poaGD69FkA1NaOeO9ra5/bqnPcXtXrK21VWzuiprXl7gkzMzMzK4CfE2ZWsIgYV3QNZmbW+9wTZmZmZlYAhzAzMzOzAjiEmZmZmRXAIczMzMysAA5hZmZmZgVwCDMzMzMrgEOYmZmZWQH8nDAz65TJkycXXUKf1dQ0p+gSzKwfcQgzs06ZMWM2zc3+uDMzs+7ycKSZmZlZARzCzMzMzArgEGZmZmZWAIcwMzMzswI4hJmZmZkVwHdHmlmnLLvs8KJL6Ddqa0cUXUK/4bbqnIXVXk1Nc2hsnL9Qjm0f5hBmZp1SV1dHfX190WWY2ULQ0NBAY+OsossYMDwcaWZmZlYAhzAzMzOzAjiEmZmZmRXAIczMzMysAA5hZmZmZgVwCDMzMzMrgEOYmZmZWQEcwszMzMwK4Ie1LgIkjQeuAGYB/wV+CZweEc0F1LIqcEtEbNjb5y6rYRPg2IjYrcrtWyKippPnCGAkUEtq87nA+Ii4K6/fC9gkIo7qVPFmZjZgOIQtOh6LiE0lbQjckped1tFOksYBRMSkak8kaSwwLiImVK6LiKlAYQEs1/AI8KEA1l7dXTiH8jFfBg6MiHsq1l8PXN/d85iZ2aLLw5GLmIh4HDgVOLjKXcblP50xFhjfyX36grH0z7rNzGwR5J6wRdPjwKqSRgIzgbOAfYEW4NqI+G4esrsFGA4g6VDgVxHxnfx6J+BM0nDbQ8DXI+JtSdOAxYHh+espEbFx6cS5t2lSRIwtW9YC/ALYEbgUOAB4OiJ2krQWcAmwNvAy8I2IeKatC5P0FWB/4EvA28ChwHzgoIj4Qt5mHHBKRIwr26+junfP7bQ0cGJEXNpxM7ctDxGPi4jxZTVdDLwJrERq+28AZ0fET9tp768DZ+TDDgKWA8ZGxL8lfYI0DL0G8Hfg4Ih4MZ97a2AOsAvwBrBLRPxD0ijgwrx+LnBC7rUzM7Ne5p6wRdPM/PcI4FOk4cE1gNWAPSStGRGPRMRo4BzgnIgYXRbAPkEKDDsAK5PmPP0AIO+zG/BI3mdjqnMd8Ctgs1zTDpIGA7flGpYnBYpfdHCcR4G1gI8B9wOfzK8nt7dTFXWPB9YjhZYzWDhWBHYHZgPvkELYth2099W53tGktpqQA1ip7W7I624Abs/LAfYgDVHXktrs8Lz8PKAe+AiwPXCFpOUW0vWamVk7HMIWTcPz3zMj4mngGOBIUu/LGGCFDvb/AikUPQK8QgoH63SzpvtJ4fDBiPgPUAMIWB24CniNNIft45IGtXWQiJhC6tHaBPhdPsbadBDCqnB8RMwm9UKN7Oax2vJcRMwgtUOpPRajivaW9B3StR5SWgSMiYhLAPLfK5ECKcBfI+LK/PVDwKj89Q6koeqpwL2k78OaPXqVZmZWFYewRdP6wMsRMVPSl4FbSb0fx5Pe6DtSA9xT1gOzIvCV7hQUES35y5ayxTVAU+k8EbECKZR1dFfn48CewDPAMKroCaumxIo6F4aWNr5ut70l7UAadt0tIua2c/yasuNGO+fatuxcq9L9tjMzsy5wCFvESFofOBm4IC/ajBS8riW9uVfeufgGaZgSSctJWgy4G/icpHXzNmcAV1bsM0bSYElD89yzrghgmqQD8vl3BJ6j45/LR4HtgBdIj+UYFhFvVHG+Nusu4nEeZdps77zsUmDniHizbJ8Apko6LG93GNBAahNoO8hOBA7LbbAKMIXUq2ZmZr3MIWzRsZGkt4DfAudGxPl5+ZWkuU6vA98EnibNDyu5FlghT1Z/ChgcES+SJs9fL+k1Uk/TkaUdIuJ5Uu/aK6Q3/rXogoiYR5qDNT6f50fArhGxoINdJwOvRsRMUuh4rMrz9UjdPa2D9v42aTL+fZKm5T9fjYj5pLbbU9LrpJ7BnfPy9hwNDCW1wQOkYdhne/6qzMysIzUtLQtz9MXMFiFjgSl1dXXU19cXXYuZLQQNDQ1Mnz6r6DJ6TG3tiD5xPbW1I1p9ILh7wszMzMwK4BBmZmZmVgCHMDMzM7MCOISZmZmZFcAhzMzMzKwADmFmZmZmBXAIMzMzMyuAQ5iZmZlZARzCzMzMzAowuOgCzKx/mTzZn/dttqhqappTdAkDikOYmXXKjBmzaW72x511pK98XEp/4LbqHLfXosPDkWZmZmYFcAgzMzMzK4BDmJmZmVkBHMLMzMzMCuAQZmZmZlYA3x1pZp2y7LLDiy6h36itHVF0Cf3GQGirpqY5NDbOL7oM60McwsysU+rq6qivry+6DLN+p6GhgcZGP1rC3ufhSDMzM7MCOISZmZmZFcAhzMzMzKwADmFmZmZmBXAIMzMzMyuAQ5iZmZlZARzCzMzMzArgEGbvkeSfh0Wcv8dmZn2H/0E2ACQtCdwtaVTRtdjCIWkw8EdJKxRdi5mZdRDCJJ0iabqkYfn1eEkvV3twSS1tLB8vaUKVxxgnaVIVdZ5SbV1VnHOSpAN76nj9xM+BSyPi7dICSRMkndbdA0uqkfQtSfdKul3S58rW7SRpiqT5kh6W9NEeON94SQ919zhlx1taUr2kjdpYP6Enf/4WloiYD/wAuKboWszMrLqesOWA/RZ2If2ZpFGSji66jq7K4WJIRNzcA8c6pZXFRwA7AYcC1wITJQ2XtApwBXAwMBL4N3BOd2voihzcxrax+nzgtoh4rJX9dgH2X5i15fOc0hPHiYhHgSckfbknjmdmZl1XTQh7GzhaUs3CLqYfGwX02xBGChEX9NCxTm5l2QLggIj4R0TcBDQDo4GhwFcj4o8R0QjcDnS7J6yLxgNjKxdK2hbYGvh+K+tqSQHthoVcG7Terl11EbBvDx7PzMy6oJoP8P4/YGNgm/KFeThxUkRMaO11Z+W5SNcCnwGagO9GxI159QhJt+Y6ngK+HhHTOjjeysClQB3wFnBYRPypi7WNBSYBZwMnkMLDIRFxm6THSW/ey0iaBsyPiFU6qkHSDqQ38KHAXcDngB2BeuCnwG7AIOCsiLgg7zMeGAc8nOs4KyKuzOuOA44EhgGPAvtERLWfFLt2RDxeZVu0AHsAZwFLAydGxKWSbgE2yduUvjefjojXIuKSvHwJ4CjgBeCfEdEC/LPs8NsD91dZc6fkIe3rgQNJ3687ImJ/SccCxwLLALdImgscHhE353ovB2YA10p6GDg/Iubmw15B6rlbrgfqWwu4BFgbeBn4RkQ80167SlqKFKi+CMwFTomIqzs6V0RMkzSyuzWbmVn3VNMTNp/US3LMQq5ld+BVYGXSm8pFZevWJ4WZFYGpwIVVHO864M68z1HAryUN6kZ9K5EC4sdIb9qnAETEhsCGwNSIGF0KYFXUcCUpdKwH7ApsFO7qQN8AABFYSURBVBH/BL5LCgQfz8f9vqR1yo65FbAZqXfmWkhzlkjBbStSD9Pz5DfuhWR8rnsX4AyAiNgtIkbnr0fnP69V7HcLcBpwTg5g75G0Cak9zlqIdX8b2JPUtttJWi8izsl1PwLslusuDcseBtSS5stNyPtenusdDyyR13VLnjB/GynQLU8Kd7+ADtv1PNLv8Kqk35nLJI3pbj1mZtY7qukJA7gK+CHwTDvbdHe48pdAA+lNfXOg/A6uZyPibgBJlwD3tHcgScPzMdbi/WGc4aSA90oX66sBjoqIeXnS96ndrOFdUq/V4qQer+a8zQ7A6qTeEPI2nwKey6/nkHoC55ed7r/AE6Q35YnAVRHxUieurUVSTWUwasfxETE7t0PVPSoRsZ2kDYD7JD0REVMBJC0D/IrUA9VuD2c3nZuDLpJeIA0jt+fzwOURUQpe00h3F54MnARsGhEtkrpbl0jf86vy6xpgqKRBEbGgnf12ArbLPwtB6lU1M7N+oqpHVETETNIbRHt3DH6km7VcBBxPGkrbvWJdc8XX1fRo1ZCG2UbnnoQxpJ62rnottwNAtWGlvRqeIA2PPQQcGRFNZfscVLbPKqQepJJHKgIYEdFM6vn6GakX7f5OTrx+ijQcWq3I562qHSR9WdLQvM+TwBRgzbxuceBG4PaI+G0nauiKKPu6mtrnAf8qe/0OaY7kDqR2fioHs2OBYyV1dW5YDdBU1tO1AimUNXew3wdI2kPSx6vYbgzwZtdKNTOzntKZ54RdQOrJKfkvaWgOSZuTeg26Y3Pgt6SenL0r1n1S0pb55oCDgQfaO1BEzM7bHJnr+xRprlV35sG094b4JrBsvuNvkKRl26shvwmuAqwTER+LiOvKjjUROEjSEnme3FPAlu0VJml14K/A0xHxE+BeOjccOYE0VFeVHPraMl3SavmxFLV52TeAU/Oy9Ulzsv6S111DCjvf6US9XdVe3W8AqwFIWj4vux34iqSROSx+G/hjRFwSEUuXBeVzSEOse3axrgCmSTogn39HUs9n+e9na+16B3CkpMGSPkIaxly8ivN9B+hw7piZmS1cVYewPHR0Y9miy4BdJN1Nurvupm7WcgbwI9JE7RWA2ZLWyOueAY4DpgFrkB550JF9gQ0kvUYKd3tHxIxu1tiqHLhOBv4OTAe26KCGqaT5RFMlTZX0mKSv5H1OB17Mf54FJkTExA7O/xJpOO9ZSa+T7jCsZt5caf9ngFckHVLtPu04CriPNJm9dAfeN4BPAq+T3vx3j4g3Ja0L7EW64eJ1SW8qP4dO0qqSpnVzHl9nnAYcJWk6af4hpDa9gxSEp5FuROgwrEp6XFLV/ymJiHmk+XXj88/Kj4BdK4YiW2vXY0i/w6+QgvcxEfG39mqQ9CVglY5+pszMbOGraWmpdmTNeoqknYCdI+IbuXdvG+CSiFitwJoGkwLSkeUPbC2SpMsi4tCi6+gsSacCF0REnxryy9/ja4GDO3HnbLmxwJS6ujrq6+t7tDazgaChoYHp07vyq/dBtbUjeuQ4A0Ffaava2hGtzpuvdmK+9awngSMkNeTXb5HuiixMnmfWZx7KK2kI6e7S/mhSXwtg8N73+CsdbmhmZr3CIawAEdFAeqSAtSEP0fXYRw/1poi4t+gazMys7/MHeJuZmZkVwCHMzMzMrAAOYWZmZmYFcAgzMzMzK4BDmJmZmVkBHMLMzMzMCuBHVJhZp0yePLnoEsz6paamOUWXYH2MQ5iZdcqMGbNpbvYnbXSkrzypuz9wW9lA5eFIMzMzswI4hJmZmZkVwCHMzMzMrAAOYWZmZmYFcAgzMzMzK4DvjjSzTll22eFFl9Bv1NaO6PYxmprm0Ng4vweqMbO+xiHMzDqlrq6O+vr6ossYMBoaGmhs9OMbzBZFHo40MzMzK4BDmJmZmVkBHMLMzMzMCuAQZmZmZlYAhzAzMzOzAjiEmZmZmRXAIczMzMysAA5hZmZmZgVwCDMzMzMrgJ+Yb9ZLJI0HrgDeAoYAfwYOjohXu3HMC4BHIuL6LtYzLiLGd/X8ZmbWde4JM+tdj0XEaGB5YApwcXcOFhFHdSWAmZlZ8RzCzAoQEQuAq4Ctiq7FzMyK4eFIs+LUAC2SRgEXAlsDc4ETSr1bkk7J280FvgkcEBF3lw4gaQIwKSImlC37BGnYcw3g76Qhzxfzuh/m47wJTF64l2dmZu1xT5hZASQtARwB3AmcB9QDHwG2B66QtFzZ5gcAo4CNgD91cNzBwG3ADXnY8wbgdkmDJW0PHAR8GtgM+GyPXpSZmXWKe8LMetdGkqYBzcAk4EjgBVJv1wF5mxpgTeDB/PofEXFclccXMCYiLgGIiEsknQGsBWwJ3BYR0wAkXQ2s2+0rMjOzLnEIM+tdj0XEpuULJNUA20bEE/n1SGBO2SYPdPOcNUALqee7pWz5gm4e18zMusHDkWbFmwgclocMVyHdNakuHiuAqZIOA8h/N5B62x4EdpK0fA56X+9+6WZm1lUOYWbFOxoYCrxC6vU6PiKe7cqBImI+sAuwp6TXgT2BnSNifkTcAvwKeIY0Kb9L5zAzs55R09LS0vFWZmYwFphSV1dHfX190bUMGA0NDUyfPqvoMhaq2toRi/w19iS3V/X6SlvV1o6oaW25e8LMzMzMCuAQZmZmZlYAhzAzMzOzAjiEmZmZmRXAIczMzMysAA5hZmZmZgVwCDMzMzMrgEOYmZmZWQH82ZFm1imTJ08uuoQBpalpTscbmVm/5BBmZp0yY8Zsmpv9SRsd6StP6jazvsvDkWZmZmYFcAgzMzMzK4BDmJmZmVkBHMLMzMzMCuAQZmZmZlYAhzAzMzOzAvgRFWbWKcsuO7zoEvqN2toRVW3X1DSHxsb5C7kaM+trHMLMrFPq6uqor68vuoxFSkNDA42NfqaY2UDj4UgzMzOzAjiEmZmZmRXAIczMzMysAA5hZmZmZgVwCDMzMzMrgEOYmZmZWQEcwszMzMwK4BBmZmZmVgCHMLNukDRe0kNF19FZklqKrsHMbKBzCDPrRTm0jS26DjMzK55DmFnvGg+MLbgGMzPrA/zZkWY9SNIk4HrgQFLYuiMi9pd0LHAssAxwi6S5wOERcbOkGuBE4ABgSWBCRJyQjzcOOAU4D/gJcFtEnChpH2DviNgxb7crcEREbCVpceAKYBtgHnB2RFzUG9dvZmbVc0+YWc/7NrAn8HFgO0nrRcQ5ETEaeATYLSJGR8TNefuvAVsAnwQE7Chp+7LjCTgY2B04PS+7FfispOH59S7AdfnrrYCRwBhgXeDUsu3MzKyPcAgz63nnRsQ/I+It4AVgVAfb7wB8BvgH8HdgReBTZeuHAvtE0gSQ/74L2FbSIGBL4Oa87k7gZ8BJpLC2FLBcD12bmZn1EIcws54XZV9XcxdiDfDj3Ds2GlgZuKBs/TMR8XYr+11H6gHbDHgkImYC5KHPi4HngYOAVzp/CWZmtrA5hJn1vOZ21r0BrAYgafm8bCKwr6RlJA0F7iZN4O/IPcD6wB68PxQJsDnwB+BGYCNg1c4Ub2ZmvcMhzKx3nQYcJWk6cGleNoE0bPgXYArwFHBZRweKiAWkIck98t8l5wNfAepJ88P+CazRM+WbmVlPqWlp8TMbzawqY4EpdXV11NfXF13LIqWhoYHp02cVXUZhamtHDOjr7yy3V/X6SlvV1o6oaW25e8LMzMzMCuAQZmZmZlYAhzAzMzOzAjiEmZmZmRXAIczMzMysAA5hZmZmZgVwCDMzMzMrgEOYmZmZWQEcwszMzMwKMLjoAsysf5k8eXLRJSxymprmFF2CmRXAIczMOmXGjNk0N/vjzjrSVz4uxcz6LocwM6vWIIDFFmv1I9CsFW6r6rmtOsftVb0+0lZjgXpgfvlCf4C3mVVrU+DBooswM+unPgq8XL7AIczMqjUU2BB4DVhQcC1mZv2Ne8LMzMzM+gI/osLMzMysAA5hZmZmZgVwCDMzMzMrgEOYmZmZWQEcwszMzMwK4BBmZmZmVgCHMDMzM7MC+GOLzKxDkrYBLgL+B7g4Is4ouKTCSToQOBVYDrgb2A94Gzgb+BowDRgfEU/m7VcD/hdYA7gHOCAiBtQnd0uqBf4GbAS8gtuqTZLuBO6JiJ9JWgy31YdI+hbwHWAJ4I/AoUAj/ait3BNmZu2StCJwM3A06WM3tpX0xWKrKpakDYETgZ2A5YElgR8ARwLbkf6R/yrwG0lD8m43AQ/n7acAJ/Vy2X3BFUBt/tpt1QZJXwdWBC7Ii9xWFSStCRwOrAusAgwBvkc/ayuHMDPryK7AXyLiDxExFzgf2Kfgmoo2D/hyRDweEf8B7iIF1H2AcyJiRkQ8C7wAbCppLWAt4McR0QKcQ3qDGDAkjQdGknrAwG3VqvyfnrOBgyOi9BE3bqsPWxv4a0TMzP8u3U8//B10CDOzjowBnih7/S/S/zIHrIh4OiIeL1v0JdKbQFttNQZ4PiKa8v5vAUtJWrKXSi6UpDHAKcD+QOmz8txWrbuQ9Nms35N0nqTRuK1a8zQwTtK6uY3GA3fSz9rKIczMOjKINNeppBEYVVAtfY6kvUj/wF9B221VuRygidQztEiTVANMAL4XEVPLVrmtKkjaANgDuA64HFgBeAAYitvqAyLiJeD/gN8AE0m907fQz36uHMLMrCNv8cF/qJYEmguqpU/JE30vBvbLE3zbaqvK5eXrFnVHAa9FxG8qlrutPuzzwNMR8Z2IuIt0s8fKwFK4rT5A0r7AvIhYJyI2AG4DrqGf/Vw5hJlZRx4GNit7vRHw74Jq6TMkjQJ+B/wkIh7Ki9tqq78CYyUtk/ddHVgceLP3Ki7MnsAXJU2TNA1YFXicdP1uqw+aRxo+AyAiFuRl9+O2qrQp8GzZ60eBTehnv4M1LS0tHW9lZgNWHk56HrgemEQaWvphRFxTYFmFyndb3QdERBxYtnwT0pDI14A1gR8CH4uItyVdBowGTic92qIhIg7o9eILJullYBywEm6rD8g9q38GPh8RL0r6JnAsqUfMbVVG0jGkifWHkuYZnkXq1foR/ait3BNmZu3KdxJtB6xDGnq7YiAHsGxb0v/Ed5f0Zv7zYEQ8AhwBnAbsDuwQEaV5KN8m3RZ/NVAPHFNA3X2G2+rDIuJfwMHATZLezF/v4bZq1aXAM6Q7kx8lzZs7tL+1lXvCzMzMzArgnjAzMzOzAjiEmZmZmRXAIczMzMysAA5hZmZmZgVwCDMzMzMrgEOYmZmZWQEcwszMbMCRNFaSn9FkhXIIMzMzMyuAH9ZqZmaFk7Q2cAmwPvBP4KiIuF/S6Lx8S+AV4NiIuDvv8zIwPiIm5denAGMjYrykScANwOeAXfIxv0z6HME5rZSwa0TctpAuz6xV7gkzM7NCSRoB3E363MQ1geuA2yQtCdwOvAusB5wL/E7SOlUe+mTgOdJHbr0NfD8i3gGWBj6Vt1k6/5nYM1djVr3BRRdgZmYD3g7AAlJIapZ0Iemz/TYEPg1sHRGzgAmSdgAOAY6s4riPRcQZAJJ+BewNkD/MeVTp6x6/GrMquSfMzMyKtirw74hoBoiIuRHxW2AF4I0cwEpeAsa0cZwlK17/sezrd4GaHqrXrEc4hJmZWdFeAcZKeu89SdIDwOvA8nm4suTjpHldAC3AoLJ1G1Ycd2Y752zO53Ews8I4hJmZWdEmkt6PTpe0iqQjgE8CzwN/Aa7Ij5QYD2wPXJ73mwp8HkDSV4HPduKcrwKzgZ0krSrp8z1yJWad4BBmZmaFysON2wAbAy8AXwd2jIjppDsbhwJ/Bb4N7BwRf8u7fh/YT1IA2wIXdeKc84EDgItJd06O75GLMesEP6LCzMzMrADuCTMzMzMrgEOYmZmZWQEcwszMzMwK4BBmZmZmVgCHMDMzM7MCOISZmZmZFcAhzMzMzKwADmFmZmZmBfh/OMlGQdARJ78AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(y='您常用的扩展数据类型是什么？',\n",
    "              data=split_and_explode(df['您常用的扩展数据类型是什么？']),\n",
    "              color='k').set(title=\"您常用的扩展数据类型是什么？\",\n",
    "                             ylabel=\"\")\n",
    "sns.despine();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们还提出了一些问题，用以了解用户最想要的功能。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(y='您现在最想看到的改进是什么？',\n",
    "              data=df,\n",
    "              color='k').set(title=\"您现在最想看到的改进是什么？\",\n",
    "                             ylabel=\"\")\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x864 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "common = (df[df.columns[df.columns.str.startswith(\"迫切想要的功能\")]]\n",
    "          .rename(columns=lambda x: x.lstrip(\"迫切想要的功能  [\").rstrip(r\"]\")))\n",
    "\n",
    "counts = (\n",
    "    common.apply(pd.value_counts)\n",
    "    .T.stack().reset_index()\n",
    "    .rename(columns={'level_0': '问题', 'level_1': \"重要程度\", 0: \"关注数量\"})\n",
    ")\n",
    "\n",
    "order = [\"无关紧要\", \"还算有用\", '至关重要']\n",
    "g = (\n",
    "    sns.FacetGrid(counts, col=\"问题\", col_wrap=2, aspect=1.5, sharex=False, height=3)\n",
    "    .map(sns.barplot, \"重要程度\", \"关注数量\", order=order)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "一眼就能看出来，优化大规模数据集的处理能力是大家最想要的，从此图还能观测出：\n",
    "\n",
    "1. Pandas 文档应该加大力度推广处理大规模数据集的支持库，如 [Dask](https://dask.org), [vaex](https://vaex.io/)，与 [modin](https://modin.readthedocs.io/en/latest/))\n",
    "2. 从对原生字符串数据类型与更少的内部复制需求来看，优化内存效率也是要值得一做的事情。\n",
    "\n",
    "紧接其后的优化需求是整数缺失值，这个功能其实已经在 [Pandas 0.24](https://pandas.pydata.org/pandas-docs/stable/whatsnew/v0.24.0.html#optional-integer-na-support) 时已经推出了，但还不是默认方式，与其它 pandas API 的兼容性也有待优化。\n",
    "\n",
    "与 NumPy 相比，pandas 略显激进。在即将推出 1.0 版里，我们将废弃很多功能，并对很多 API 进行翻天覆地的改变，好在大部分人都能接受这样的改变。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "是    94.89%\n",
       "否     5.11%\n",
       "Name: Pandas 能满足您的需求吗, dtype: object"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Pandas 能满足您的需求吗'].value_counts(normalize=True).apply(pct_format)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "不少人，甚至 pandas 维护人员都觉得 pandas API 的规模太大了。为了量化这个问题，我们还向用户提出了关于 pandas API 规模的问题，看看大家觉得是太大，还是太小，还是刚刚好。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAEeCAYAAACdYvI/AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAActUlEQVR4nO3deZhcVbnv8W9IAiEQNEILYYyKvnAE4YAQQHE8Ih4RRFCPchVExAmF43hBQK4yOCAgjqAi4IAiKOBFEDnKoAziiIq+KgImUTBExiRkIH3+WLulKLrTtZpOV3X4fp4nT7p2rb33W5X0/tXaa+1dE/r7+5EkqVOrdbsASdL4YnBIkqoYHJKkKgaHJKmKwSFJqmJwSJKqGBzSShARUyNimzHa13oRMXEs9iWBwSE9KhHxsoj49SBP/Qdw2RiVcQPwmdqVIuK5EfGHiNiwcr1JBtVj26RuFyCNc/c1f4iI1YGJmbkIuBF4YkRslJlzI2ISMCEzl66EGpYDfxnBeouBpwB3DNUgImYBF7YsuhG4Ejg6IpYBA1cQTwb+JzP/c5BtbADsDPwpM387gjrVYwwOrZIi4kzg1sw8Zgx3+zzgrIh4sHk8F7g+IgAmAsfS9AwiYhc665FckJn/Z5g2k4F7R1BvP3BvZj44TJvbM3PbiHge8JHMPA44rrVRRLwP2Lp95Yh4IXAuJXC2iYjDMvPsEdSqHmJwSCMQEVsDnwNWB54aET8EDgI2Bz4EfDgz746IvYFXAvtlZuv9fZYDyzLz8SvYxzFAtC2bAixtO9ivCTzQ1m4SMCkzH2gerw1MABZk5vKm2WRgUdt6awBTm9ruA5a0lbWsafci4B+ZOXCabjowf5CX8S7giMw8rQmerwAGxzhncEgjcxPwYmAnSlC8lPLpfAnwOOAVwBnAgcClmdkfEZMyc1mz/uIO99N+4L4fmNj0Ylp9OSK+3LbsNmBm8/ORwPsB2teNiMFuWPcJ4D0rqOsdwA+BgeB4AqWH1e5c4IqW2r053irA4NCYiogDgLcBfwOeTznwvDEz/9Q8H8DpwDOB24H3ZOZ3muf6KYPOxwLbAD8C9s3MRRGxHvAl4IXA9ZSD1K3NehOBk4D9KBNCzgPeMvDJOyIOoxwkpwNXAwdk5u0reh3NJ/4FzWmp/ubPgcDxlE//e0TE8cAawI4R8aGm7pObTXR6AG1vtx4ldJa2PP47JchaZ3GtzsN/v08ATqTpMTT2b+rZAvhHs2y1puaH9UQGsQ4lmAZMp5yOepjMPAv+9W/wYUqPQ+OcwaFu2AE4CjiMcjD9RkQ8szmVcyZloPe/gF0pYwbfbfmk/nnKQf5W4PKm3ZcpYwfTKAfPFwKnAb9s1jkIeA1lDGIRcAmwL3BuE1QnAy8B/gB8EjiaEm6d2pRy4N4hMz8LEBGfA76Qmb+o2M6wMvPu1scRsRPlk/76zf6vbZ5a1rbePe3biojnAguBfTLzhMpS1gXmtTyeDvxzBe0/CKxN+ffWOGdwqBvmAMc1p2+OoHxy3bT5ey/KQO9TgBmUMJgBzG7W/XxmXggQEZcDmzafZvcGXpSZNwM3R8QbW/b3deAbwBRgR8r4wsD5msXN4ymUHs7LKWMBKxQRq1EC6khgY8p4x6Rm+ZrAGyk9m9Z11mxmXI2mA4CzKD2MIymnzIYVEU+mhOXLgXMi4uzMHOxU01CmA5e3nfbaNSK+DmyUmX9r2dc6wKHA1ivh9asLvI5D3TCnZaB44GC1QfP3PpTexDcpp1CgzEga8IOWnxdTDvLrUQZ6Z7c81zo9dVPKDKZfUXofiwa2mZm3Uk7ZHE4Z3P1+y35XZCvKNNX7gWsy8+2UU2x/pUxvXULpLc2LiCURMYdyvcWoiYhdgRcApwAfB2a1BeaKfAY4KzO/Tzl99IWIGCowN4qIU4BDgNWaAfqZmTklM6dQgvLxwJaUEG6f3rsz8OvM/GvFy1MPMzjUDZs1n8yhHNQB/hYRMykHtJdl5lbAuwdZd7Bpp/OBB4HWC9k2bfn508ANmTkjM/cC/jTwRERsDPwhM2dRTvfcTjkdtkKZeSNl4PnjLcv2Ap7cbGO3zNwY+CzwqczcuHlNoyIiNqH0oo7JzHmZ+Q/KgPUpzbUXK1r3JOCpwHubRUcAmwGnDhIek4G5mXkY5X1cvXlNcyNiThOIcyhjVnsBdwwyvfd64PUjfKnqQQaHumEGcFQTFMcBP83M2ZRz4BOAdSJiS8qBEYY5ddSMf1zUbPPJzQD8Li1NpgGrR8SGEfFOyoyngW1uAVzWTBWdRvnE3NFV0c3But3Tm7+Pbz79v5GWcBkNEbEF5SK8a4H3NWMVZOY5lIP7D5ppwO3rbRgRF1EO4ns3023JzAWUU1avAr4VEa1ThNdo+fnHwPMy88DMXL8Jw40zc6PMfAKlt9Xa6xuwB3DMo3vV6iUGh7rhOsoB9tfARsBrAZqrij8OfJsygH05cA+wXQfbfCtlptGvKAfGS1qeey9lBtdNwLOAcwa2mZmXU2ZcfYVyeuvplE/unXpYyGTmL4GnAb+jnLqaArw6ItZsW2814HER8cBQfyhjFv8ah2xu9fEWyvt3dmbuS3m/LmqClsw8nDJ76VsR8Z0opkXEycAfKT2xnTLzN211/6l5j7YHfhcR+zRPXUs51URmLsvM+9vfgIiYHhHbUt73R8ysokxZ3n8F76HGmQl+57jGUtMbOCAzn9flUh615mrpfSljNq+IiJcBzwF2a5oc0vx9MiUgD87M7zbr7gJ8r4MLALdqAoKmV/Ql4J2ZeXFLuxOAH2TmD1uW7UIJnv0y865mltdc4GOZ2X5tSOs+n0CZtntiZt7U4fvwNOC3lFNS+zmWseozODSmVrHg2Jcy/ff0zJwdEftTehsXA9cOTABoxnPeApyfmUPeF6rDfU5ouwK9J0TExGFuXaJViMEhSariGIckqcqqHhyTKFMmvdBRkkbJqn5A3Ri4Zf78+1m+vPdPyU2fPpW77lrY7TKGNV7qBGtdGcZLnTB+au3FOvv6pg05DX5V73GMK5MmjY8vVRsvdYK1rgzjpU4YP7WOlzoHGBySpCoGhySpisEhSapicEiSqhgckqQqq/p0XADWXXftbpfQsb6+ad0uoSPjpU7oTq0LFy5iwYJlwzeUxqHHRHDMmjWLOXPmdLsMPYbMnTuXBQvu63YZ0krhqSpJUhWDQ5JUxeCQJFUxOCRJVQwOSVIVg0OSVMXgkCRVMTgkSVUMDklSFYNDklTF4JAkVTE4JElVDA5JUhWDQ5JUxeCQJFUxOCRJVQwOSVIVg0OSVMXgkCRVMTgkSVUMDklSlREFR0RMiYhpo12MJKn3jbTHMQu4NyLW73SFiHhPRDx3mDaTI8JekCT1sEkjXK8fWJKZd1SssydwF3DlCtp8DnhNRCwGlg/y/HRK2E3OzGUV+5YkjZKRBsfqwH2V6ywD7lxRg8w8CDiofXlzWuxE4OXA0YaGJHVPR8EREVOApZn5YLNoCvBAW5uJlJ7AAxGxDvBgZi5oaTIRWNjSfnVgLUrPpbVd+773BD4NXAVsmZn/7KRmSdLK0WmP4zZgrYgY+KQ/GZgaEffy0CmlScC9wIbAScD+EfFgyzZWBy6OiIH2E5pl76X0Jh4hIg4H3g8clJnndVirJGkl6ig4MvNhg+DNAf144G2Z+dVBVjm4Oe000H4CMB/4RGYe17Z8wgp23Q9cYWhIUu8Y6Qym5wPfZpDxCIDMbB/Y3hW4HzgoItZoadc/SNtWjmVIUo+pDo6I2ALYEngd8JSI2KuD1Y4EjgN+BBxVu09JUu+oCo6ImAScBnw0MxcC7wBOj4gZK1jnzcD6wBnA+4A3RMSuIy9ZktRNHQdHM2vqTGAqMA8gMy8AvglcFREzB1nnrcAJwKszc2lm3gnsD1wYES961NVLksZcp9NxNwTOApZQeg3nRUR/Zp4LHEqZHXVdRHyAEi7bA8cCWwG7Z+YfBraVmZdHxDsoM6zOAt7fPsU2IvqATYHtgNaZWZKkLhu2xxER2wO/AX4G7JmZPwJeAXwwIiY3A9xvoQTKR4AdgHOAO4CtM/On7dvMzK9RBsyfCzxrkN32NfvbHfjKSF6YJGnlmNDf3z9so4jYJDNnty2bnJlL25atlZkLImJqMwYy3HYfsY2W5zYHbs7M4Qsc2kzgllmzZjFnzpxHsRmpzty5c5k3r+7mCn1906rX6YbxUieMn1p7sc6+vmlDXirR6XUcswdZ9ogD/sAV4J2ExlDbaHnuz51sQ5I0trwTrSSpisEhSapicEiSqhgckqQqBockqYrBIUmqYnBIkqoYHJKkKgaHJKmKwSFJqmJwSJKqGBySpCoGhySpisEhSapicEiSqhgckqQqBockqYrBIUmqYnBIkqoYHJKkKpO6XcBYuP7667tdgh5jFi5c1O0SpJXmMREc8+ffz/Ll/d0uY1h9fdOYN+++bpcxrPFSJ4yvWqXxwlNVkqQqBockqYrBIUmqYnBIkqoYHJKkKgaHJKmKwSFJqmJwSJKqGBySpCoGhySpisEhSapicEiSqhgckqQqE/r7e/+usY/CTOCWbhchSWNt4cJFLFiwbMTr9/VNmzDUc4+J26rPmjWLOXPmdLsMSRozc+fOZcGClfOVAp6qkiRVMTgkSVUMDklSFYNDklTF4JAkVTE4JElVDA5JUhWDQ5JUxeCQJFUxOCRJVQwOSVIVg0OSVMXgkCRVMTgkSVUMDklSFYNDklTF4JAkVTE4JElVDA5JUhWDQ5JUxeCQJFUxOCRJVUY1OCLi5oh4SkX7L0XEG9uWvTki9hnNuiRJo2fScA0iYgLwIHBT21N9wJeA44E1M3Me8ACwJCKuADYDFrS0nwrcDjwHmJGZswfat213D+DLzb43B97c7L/VzzPzW8PVLkkafcMGR2b2R8QyYNvMXDawPCKOBCYD+wAvBV4F9Dd/lgBvyszLW9o/GzgO2Ai4AXhiS/tW2wD/0/x8D/ATYGC/mwMnAIdWvUpJ0qgZNjgay4FtImIN4EbgOuBiYBGwmEf2GpYD60XEqzLz3Ij4HvBDSkgM1p6I+BTwQmBD4CcRAfDBzDy/eX434J3AKzPz/1e9SknSqKkZ45hMOYX0MuC3wH3DtF8KfDgiXgA8DfjlMO3fDXwcOCMzt6L0Nv7e8vypwNsNDUnqrprg+BlwLvBF4JQO2t8DvA34brPO4hU1zswlwAuA70XE6sDWwO8iYqBXNB+YBxARazRjL5KkMVY7q+oPwBQGOdU0hJspp8OGbR8Ra1KC4/vAzpSgOg6YExG3As8ELmp+ng1sXFW5JGlUdDrGAbA2cBRlYPoE4OoO1vkocDhlbOJtw7TdgHJ6613AFsA5mfkF4BCAiLgOOCQzf1ZRsyRplNX0OE4Fzgc+A0wA1muWrwFMHKT96ykzqE4GLgD+fUXtM/OWps0uwH7AJRW1SZLGSE1wHAJ8KDP7M3M34M5m+Q+BEwdpfzawR9P+MODKZvk8YP8V7GdTSkBdGhEzKuqTJI2BToNjNWBhZi4GiIinU66p6M/M2Zn584hYm9ILWTaw3cy8u2m/CbBd035hZl4WEZMp4xTLmjZbUMLl85n5SuA7NKe3mrbrUk5lSZK6aNjgaGYv3cbDL9R7DRA0p5MiYlfgbsqU239QehULW9pvRbkC/Oym/VRKj+VpwLXNPk4FTsrMzwBk5lHA0c31Gw8A9wN/HOkLlSSNjgn9/e0Xbo9MRKyZmYsq2k/NzIUtjydk5iOKiYiJwGaZ+ZcRlDUTuGXWrFnMmTNnBKtL0vg0d+5c5s0b7nK7ofX1TRvykodRC44eNRODQ9Jj0MoMDm+rLkmqYnBIkqoYHJKkKgaHJKmKwSFJqmJwSJKqGBySpCoGhySpisEhSapicEiSqhgckqQqBockqYrBIUmqYnBIkqoYHJKkKgaHJKmKwSFJqmJwSJKqGBySpCoGhySpyoT+/v5u17AyzQRu6XYRkjTWFi5cxIIFy0a8fl/ftAlDPTdpxFsdR+bPv5/ly3s/IPv6pjFv3n3dLmNY46VOsNaVYbzUCeOn1vFS5wBPVUmSqhgckqQqBockqYrBIUmqYnBIkqoYHJKkKgaHJKmKwSFJqmJwSJKqGBySpCoGhySpisEhSarymLjJ4brrrt3tEob0aO9gKUlj7TERHLNmzWLOnDndLmNQc+fOZcGC8XNXTEnyVJUkqYrBIUmqYnBIkqoYHJKkKgaHJKmKwSFJqmJwSJKqGBySpCoGhySpisEhSapicEiSqhgckqQqBockqYrBIUmqYnBIkqoYHJKkKgaHJKmKwSFJqmJwSJKqGBySpCoGhySpyoiCIyKmRMS00S5GktT7RtrjmAXcGxHrd7pCRFwYEQcP02ZyRNgLkqQeNmmE6/UDSzLzjop1FgNLhmnzOeA1EbEYWD7I89MpYTc5M5dV7FuSNEpGGhyrA/dVrjNYEDxMZh4EHNS+vDktdiLwcuBoQ0OSuqej00LNmMbElkVTgAfa2kyMiClty46NiO3alk2IiFMi4gkd7ntP4HfAWsCWmXlaJ+tJklaOTnsctwFrRcTAJ/3JwNSIuJeHehKTgHuBDQEi4vHA+4Cvt24oM/sjYjPgA8C7V7TTiDgceD9wUGae12GtkqSVqKPgyMyHDYI3B/Tjgbdl5leHWG0v4MbMvGmQ544AboiIkzNzzgp23Q9cYWhIUu8Y6Qym5wPfZpDxiBZvAs4a7InM/D3wHeD/DrMfxzIkqcdUB0dEbAFsCbwOeEpE7DVIm1nA9sBQvRGATwEHdjrWIUnqDVXBERGTgNOAj2bmQuAdwOkRMaOt6U7AGZl511DbysyfUk53Ta4rWZLUTR0HRzOr6kxgKjAPIDMvAL4JXBURMwfaZuYngUOG22ZmHlt5LYgkqcs6GhyPiA0p4xVLKDOlzouI/sw8FziUcl3HdRHxAeDMzHwwM/ubdWcALwCeAXQ0yB0RfcCmwHbAg3UvSZK0Mg3b44iI7YHfAD8D9szMHwGvAD4YEZMzsz8z30IJlI8AO7RtYhGl93E1cGmHdfU1+9sd+EqH60iSxsCwPY7M/HlEbJuZs1uWXdksW9qy7OyIOD8zF7Stfzewc01RmXlTRDwVuHmg5yJJ6g2dXscxe5BlSwdZtqB92Uhl5p9Ha1uSpNHjnWglSVUMDklSFYNDklTF4JAkVTE4JElVDA5JUhWDQ5JUxeCQJFUxOCRJVQwOSVIVg0OSVMXgkCRVMTgkSVUMDklSFYNDklTF4JAkVTE4JElVDA5JUhWDQ5JUxeCQJFWZ1O0CxsL111/f7RKGtHDhom6XIElVHhPBMX/+/Sxf3t/tMiRpleCpKklSFYNDklTF4JAkVTE4JElVVvXB8YkAq602odt1dGy81Dpe6gRrXRnGS50wfmrtwTpnAnOAZe1PTOjvX6VnGz0buLrbRUjSOPUk4Nb2hat6cKwB7AD8HXiwy7VI0njzmOxxSJJGmYPjkqQqBockqYrBIUmqYnBIkqoYHJKkKgaHJKmKwSFJqmJwSJKqrNL3qoqIFwOfAtYCPp2ZJ3S5nm2Ar2bm1s3jKcAXgN2BPwP7ZeZfmueeCXwRmAF8Ezg0M8fkas2IOAj4MLAecBnwOuBu4OPA64HbgQMy8+dN+ycDZwFbAJcDB2bmmHy1YUQ8Ffh/wMbAVU3dS3ux1mb/fcDvgB2Bv/ZanRFxDrAb5T0EOB04ptfqbKv5EuDyzPxERKzWa7VGxGuBk9oWrw9sBhzaS7V2apXtcUTEDOB84DDK/VZ2j4jduljPjsCFwLSWxScAmwCbUn45v9q0XbNpexolONYF3jRGde4AHAnsCTwRmAp8AHgH8BLKf+TXAudExORmtfOAnzTtbwGOGqNa1wIuBb4LvAHYCXhfL9ba4nSgr/m5F+vcAXhGZm7Q/Dm6R+sEICLeQPkd+WSzqOdqzcyvt7yfG1A+iF0D7N1rtXZqlQ0Oyj/KLzLze5m5BDgF2K+L9bwbeHvbsv2AD2Xmosz8PrBWRDwJeD7l/jCfz8zlwImMXe1LgVdm5g2ZeRflwPykZv8nZub8zPwN8Hvg2RHxb8C/Na+jv6n1tWNU6wzghMw8JzNvBi4CokdrJSIOAB5H6WnQa3VGxHRgzcyc2/ZUT9XZUu8MSu/i4MwcuJ9ST9baUvME4HjKB5yernVFVuXg2BT4Wcvjv1CSvVv+i3KKAvjXaao+Bq9xU+DnLaemxqz2zPxVZt7Qsug/gSsZ+v3cFLgpMxc26/8TWCcipo5BrX/OzC8CRMTTKb2yr/VirREx0KvcHxj4d+21OncE1oyIWyLizog4JyKm9WCdA06l3Lz08Ig4OSI26OFaB+wO3J+ZPxkHtQ5pVQ6OiZTz8gMWAI/vUi0MMj4xEViemfe2LBuosSdqj4hXU/4Tn76CmtqXAyykfLIeExHxEuAK4B7KOEdP1dp8yjwTODwzZ7c81VN1Uo4Hn+Chg9c6lNOUvVYnEbE9sC/l9O5plDGDqyh3xO6pWtv8Nw+Nd/Tc+9qpVTk4/snD3+ipwPIu1TKYhcDSiFinZdlAjV2vvRmc+zTwumZQbqia2pe3PjcmMvMSYCPgNsqpi16r9VDg75l5TtvynqozMy/JzOMyc3HzafezlE/IPVVnY1fgV5n57sy8lDJusBEl7HqtVgAiYiawNfC9ZlEvvq8dWZWD4yfAc1oe70g5sPSEpgdyDeUXgGY2yPaUGq8Bdo6IgVlvY1p7RDyeMl5wXGb+uFk81Pv5a2BmRDyhWXdzYHXgzjGoc/OI2AmgGcf6FrBtD9b6KmC3iLg9Im6nTIi4odl3z9QZEXs1Y2wDNqacCuq19xPKWNxfBh5k5oPNsit7sNYB+wHnN7VCb76vHVmVp+NeDawdEcdQTmMcCRzdzYIGcTpwUkTcB7wUWAL8NDOXR8SNwGci4kzgY8DXx6KgZlbHd4HrMvOUlqe+CHw7Iv4EbNn8uTQzF0bEt4AzIuJ4ynTYc1t+OVam9YCLmhlrs4HXAD8GLuilWjNzl9bHEXEr8Dxgw16qE3gGsF9EHNzU9i7gDMrvUi/VCXAJcHREPC0z/xgRbwXmU37Pe63WAXvz8GNQL/5OdWSV7XE0n+hfAmxFOeVyemae3d2qHi4zv0GZRvhJYBtgz2YWFZRPJ5Mp/7l+RJm6OxZ2p3zl7j7NAOmdEXF1Zl4DHAIcC+wD7JGZA+dh30WZMvhlyjeG/fdYFJqZ11F+Ea+iBMc9wNG9WOtgerDOjwGLm/1dBHwF+EQP1klzvdPBwHkRcWfz8769WCtARKxL+R2/puU19GStnfAbACVJVVbZHockaeUwOCRJVQwOSVIVg0OSVMXgkCRVMTikcSIiZkaE0yDVdQaHJKmK13FII9TckfezwHbAzZQv27qyuUvrZ4EXUG6h/p7MvKxZ51bKF/Zc0Tw+BpiZmQdExBXAucCzgJc323wl5TYUg32Jz96ZecFKennSkOxxSCPQ3G78MuBayq0ivgpc0Nz6+kLKFdjbUu6EelFEbNXhpj8I/JZyx4O7gSMy8wFgOuXKY5qfpwMXj86rkeqsyveqklamPSg3ADyiubfYqZRbQ+wA/DvwH5l5H3BmROwBvJny7XTD+Wk2X3EcEV+jfI8LmXl3c/NJWm5LIXWFPQ5pZDYBbhu4t1hmLmnuPbY+8I8mNAb8mfL9FoNp/3KeH7T8vBiYMEr1SqPG4JBG5q+UW1//63coIq4C7gCe2JzKGvBUHrotfj/li3oG7NC23XsZ2vJmP4aJusrgkEbmYsrvz/ERsXFEHEK5LflNwC+A05vpswdQbpl/WrPebB76DpbXAjtV7PNvwP3AnhGxSUTsOiqvRKpkcEgj0JyKejGwM/B74A3AyzJzHmVG1BqUL+R5F7BXZg583/wRwOsiIim3sP9UxT6XAQdSvibgZuCAUXkxUiWn40qSqtjjkCRVMTgkSVUMDklSFYNDklTF4JAkVTE4JElVDA5JUhWDQ5JU5X8BJRlBwgXO+bAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "renamer = {\"pandas 接口太大了（难找到要用的方法或难记）还是太小了（需要提供更多功能）\": \"pandas 接口太大吗？\"}\n",
    "sns.countplot(y=\"pandas 接口太大吗？\",\n",
    "              data=df.rename(columns=renamer),\n",
    "              color='k').set(title=\"pandas 接口太大吗？\",\n",
    "                             ylabel=\"\")\n",
    "sns.despine();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "最后，我们还提出了满意度的问题，从 1 （非常不满意）至 5 （非常满意）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(y='Pandas 满意度',\n",
    "              data=df[['Pandas 满意度']].dropna().astype(int),\n",
    "              color='k').set(title=\"Pandas 满意度\",\n",
    "                             ylabel=\"\")\n",
    "sns.despine();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "大多数人都对 pandas 非常满意。满意度的平均分为 4.39。我们希望以后能跟踪这一数据的变化。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "My Env",
   "language": "python",
   "name": "myenv"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  "toc": {
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   "nav_menu": {},
   "number_sections": true,
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   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
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   "toc_position": {},
   "toc_section_display": true,
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  },
  "varInspector": {
   "cols": {
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    "lenVar": 40
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   "kernels_config": {
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    "r": {
     "delete_cmd_postfix": ") ",
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     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
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   },
   "types_to_exclude": [
    "module",
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    "builtin_function_or_method",
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    "_Feature"
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 "nbformat": 4,
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}
